GraphPipe vs numericaal: What are the differences?
GraphPipe: Machine Learning Model Deployment Made Simple, by Oracle. GraphPipe is a protocol and collection of software designed to simplify machine learning model deployment and decouple it from framework-specific model implementations; numericaal: Machine learning for mobile & IoT made easy. numericaal automates model optimization and management so you can focus on data and training.
GraphPipe and numericaal can be primarily classified as "Machine Learning" tools.
Some of the features offered by GraphPipe are:
- A minimalist machine learning transport specification based on flatbuffers
- Simple, efficient reference model servers for Tensorflow, Caffe2, and ONNX.
- Efficient client implementations in Go, Python, and Java.
On the other hand, numericaal provides the following key features:
- MODEL RESOURCE OPTIMIZATION - We automatically run multiple toolchains to give you the best speed, power and memory tradeoff on every model change.
- CROSS-PLATFORM MODEL ANALYTICS - We measure on-device speed and power usage to help you evaluate and compare models across hardware platforms.
- BOTTLENECK IDENTIFICATION - We help you pinpoint performance bottlenecks and focus your model optimization on layers that matter the most.
GraphPipe is an open source tool with 643 GitHub stars and 91 GitHub forks. Here's a link to GraphPipe's open source repository on GitHub.